Annual variation of source contributions to PM10 and oxidative potential in a mountainous area with traffic, biomass burning, cement-plant and biogenic influences.

Toxicity of particulate matter (PM) depends on its sources, size and composition. We identified PM10 sources and determined their contribution to oxidative potential (OP) as a health proxy for PM exposure in an Alpine valley influenced by cement industry. PM10 filter sample chemical analysis and equivalent black carbon (eBC) were measured at an urban background site from November 2020 to November 2021. Using an optimized Positive Matrix Factorization (PMF) model, the source chemical fingerprints and contributions to PM10 were determined. The OP assessed through two assays, ascorbic acid (AA) and dithiothreitol (DTT), was attributed to the PM sources from the PMF model with a multiple linear regression (MLR) model. Ten factors were found at the site, including biomass burning (34, 40 and 38% contribution to annual PM10, OPAA and OPDDT, respectively), traffic (14, 19 and 7%), nitrate- and sulphate-rich (together: 16, 5 and 8%), aged sea salt (2, 2 and 0%) and mineral dust (10, 12 and 17%). The introduction of innovative organic tracers allowed the quantification of the PM primary and secondary biogenic fractions (together: 13, 8 and 21%). In addition, two unusual factors due to local features, a chloride-rich factor and a second mineral dust-rich factor (named the cement dust factor) were found, contributing together 10, 14 and 8%. We associate these two factors to different processes in the cement plant. Despite their rather low contribution to PM10 mass, these sources have one of the highest OPs per µg of source. The results of the study provide vital information about the influence of particular sources on PM10 and OP in complex environments and are thus useful for PM control strategies and actions.

Aerosol source apportionment uncertainty linked to the choice of input chemical components.

For a Positive Matrix Factorization (PMF) aerosol source apportionment (SA) studies there is no standard procedure to select the most appropriate chemical components to be included in the input dataset for a given site typology, nor specific recommendations in this direction. However, these choices are crucial for the final SA outputs not only in terms of number of sources identified but also, and consequently, in the source contributions estimates. In fact, PMF tends to reproduce most of PM mass measured independently and introduced as a total variable in the input data, regardless of the percentage of PM mass which has been chemically characterized, so that the lack of some specific source tracers (e.g. levoglucosan) can potentially affect the results of the whole source apportionment study. The present study elaborates further on the same concept, evaluating quantitatively the impact of lacking specific sources' tracers on the whole source apportionment, both in terms of identified sources and source contributions. This work aims to provide first recommendations on the most suitable and critical components to be included in PMF analyses in order to reduce PMF output uncertainty as much as possible, and better represent the most commons PM sources observed in many sites in Western countries. To this aim, we performed three sensitivity analyses on three different datasets across EU, including extended sets of organic tracers, in order to cover different types of urban conditions (Mediterranean, Continental, and Alpine), source types, and PM fractions. Our findings reveal that the vehicle exhaust source resulted to be less sensitive to the choice of analytes, although source contributions estimates can deviate significantly up to 44 %. On the other hand, for the detection of the non-exhaust one is clearly necessary to analyze specific inorganic elements. The choice of not analysing non-polar organics likely causes the loss of separation of exhaust and non-exhaust factors, thus obtaining a unique road traffic source, which provokes a significant bias of total contribution. Levoglucosan was, in most cases, crucial to identify biomass burning contributions in Milan and in Barcelona, in spite of the presence of PAHs in Barcelona, while for the case of Grenoble, even discarding levoglucosan, the presence of PAHs allowed identifying the BB factor. Modifying the rest of analytes provoke a systematic underestimation of biomass burning source contributions. SIA factors resulted to be generally overestimated with respect to the base case analysis, also in the case that ions were not included in the PMF analysis. Trace elements were crucial to identify shipping emissions (V and Ni) and industrial sources (Pb, Ni, Br, Zn, Mn, Cd and As). When changing the rest of input variables, the uncertainty was narrow for shipping but large for industrial processes. Major and trace elements were also crucial to identify the mineral/soil factor at all cities. Biogenic SOA and Anthropogenic SOA factors were sensitive to the presence of their molecular tracers, since the availability of OC alone is unable to separate a SOA factor. Arabitol and sorbitol were crucial to detecting fungal spores while odd number of higher alkanes (C27 to C31) for plant debris.

The unexpected role of bioaerosols in the Oxidative Potential of PM.

Bioaerosols represent up to 15-25% of PM by mass, but there is currently no assessment of their impact on Oxidative Potential (OP), or capacity of particulate matter (PM) to produce damaging oxidative reactions in the human lungs. Here, the OP of selected bioaerosols (bacteria cells vs fungal spores) was assessed through the cell-free DTT assay. Results show that bioaerosols induce Reactive Oxygen Species (ROS) production, varying along the microorganism type, species, and concentration. Fungal spores show up to 10 times more ROS generation than bacterial cells. At the highest concentrations, fungal spores present as much oxidative reactivity as the most redox-active airborne chemicals (Copper, Naphtoquinone). Moreover, bioaerosols substantially influence OP of ambient PM and that of its chemical constituents: in presence of A. fumigatus spores, the OP of Cu/NQ is increased by a factor of 2 to 5, whereas, 104 and 105 S. epidermidis bacterial cells.mL-1 halves the OP of Cu/NQ. Finally, viable and gamma-rays-killed model bioaerosols present similar oxidative reactivity, suggesting a metabolism-independent cellular mechanism. These results reveal the importance of bioaerosols for PM reactivity. PM toxicity can be modified due to bioaerosols contribution or by their ability to modulate the OP of toxic chemicals present in PM.

Large chemical characterisation of PM10 emitted from graphite material production: Application in source apportionment.

This work focuses on emissions from industrial sources that are still poorly understood in Europe, especially the "carbon industry". The study is based on two intensive sampling campaigns performed in a graphite material production plant for 2weeks in July 2013 and November 2013 in alpine valleys. The chemical characterization of PM10 was conducted at three sampling sites (outdoor and indoor sites) located inside one industrial area, which is considered as the highest emissions source of polycyclic aromatic hydrocarbons (PAHs) in the Arve valley. The identification of specific tracers among metals and trace elements is commonly used to characterize industrial emissions. In our study, original enrichment factors relative to the "rural exposed background" have been calculated, and the metallic fraction was not affected by this industrial source. In contrast, the organic fraction of PM10 has a number of features, providing a complete organic source profile and referred to as the "carbon industry". In particular, polycyclic aromatic sulfur heterocycles (PASH) have been largely detected from fugitive emissions with rather large concentrations. The average concentrations of benzo(b)naphtho(2,1-d)thiophene (BNT(2,1)) reached 2.35-6.56ng·m(-3) and 60.5-376ng·m(-3) for outdoor and indoor sites, respectively. The use of this reference profile in the chemical mass balance model (CMB) applied to samples collected in two sites near industrial areas shows that this source had an average contribution of 6% of the organic matter (OM) mass during the sampling period during the winter of 2013.

Source apportionment of PM10, organic carbon and elemental carbon at Swiss sites: an intercomparison of different approaches.

In this study, the results of source apportionment of particulate matter (PM10), organic carbon (OC), and elemental carbon (EC) - as obtained through different approaches at different types of sites (urban background, urban roadside, and two rural sites in Switzerland) - are compared. The methods included in this intercomparison are positive matrix factorisation modelling (PMF, applied to chemical composition data including trace elements, inorganic ions, OC, and EC), molecular marker chemical mass balance modelling (MM-CMB), and the aethalometer model (AeM). At all sites, the agreement of the obtained source contributions was reasonable for OC, EC, and PM10. Based on an annual average, and at most of the considered sites, secondary organic carbon (SOC) is the component with the largest contribution to total OC; the most important primary source of OC is wood combustion, followed by road traffic. Secondary aerosols predominate in PM10. All considered techniques identified road traffic as the dominant source of EC, while wood combustion emissions are of minor importance for this constituent. The intercomparison of different source apportionment approaches is helpful to identify the strengths and the weaknesses of the different methods. Application of PMF has limitations when source emissions have a strong temporal correlation, or when meteorology has a strong impact on PM variability. In these cases, the use of PMF can result in mixed source profiles and consequently in the under- or overestimation of the real-world sources. The application of CMB models can be hampered by the unavailability of source profiles and the non-representativeness of the available profiles for local source emissions. This study also underlines that chemical transformations of molecular markers in the atmosphere can lead to the underestimation of contributions from primary sources, in particular during the summer period or when emission sources are far away from the receptor sites.